Residential rooftop‐mounted solar photovoltaic (PV) panels are being installed at an increasing rate, both in New Zealand and globally. There have been concerns over possible issues such as overvoltage and overcurrent. These PV systems are mostly connected at low voltage (LV). This study presents a case study of simulating the entire LV network from a single utility, comprising 10,558 11 kV–415 V transformers and their associated distribution feeders. These results are also presented by network type. Various solar PV penetration levels are added to the model and the power‐flow results are presented. From these results, possible maximum limits of solar PV penetration are investigated and measures to alleviate overvoltage problems are simulated. The effect of using PV inverters with voltage regulation is simulated. Results show that some minor overvoltage problems can be expected in the future, particularly in urban areas. However, in most cases the overvoltage would not be much higher than the statutory limit of 1.06 p.u.

There is a growing use of High Voltage Direct Current (HVDC) globally due to the many advantages of Direct Current (DC) transmission systems over Alternating Current (AC) transmission, including enabling transmission over long distances, higher transmission capacity and efficiency. Moreover, HVDC systems can be a great enabler in the transition to a low carbon electrical power system which is an important objective in today’s society. The objectives of the paper are to give a comprehensive overview of HVDC technology, its development, and present status, and to discuss its salient features, limitations and applications.

In this paper, a hybrid optimization algorithm is proposed to solve multiobjective optimal power flow problems (MO-OPF) in a power system. The hybrid algorithm, named DA-PSO, combines the frameworks of the dragonfly algorithm (DA) and particle swarm optimization (PSO) to find the optimized solutions for the power system. The hybrid algorithm adopts the exploration and exploitation phases of the DA and PSO algorithms, respectively, and was implemented to solve the MO-OPF problem. The objective functions of the OPF were minimization of fuel cost, emissions, and transmission losses. The standard IEEE 30-bus and 57-bus systems were employed to investigate the performance of the proposed algorithm. The simulation results were compared with those in the literature to show the superiority of the proposed algorithm over several other algorithms; however, the time computation of DA-PSO is slower than DA and PSO due to the sequential computation of DA and PSO.

This paper presents a method to achieve optimal active and reactive power contributions from each energy storage system in an unbalanced distribution network to minimize power loss, while ensuring network current and voltage constraints are satisfied. By modelling loads as either constant current or constant impedance, the AC optimal power-flow is transformed into a non-iterative convex optimization problem. The application of capacity constraints, voltage constraints, and energy storage constraints in an unbalanced three-phase four-wire system is considered, addressing specific issues pertaining to unbalanced networks such as voltage unbalance and neutral voltage displacement. The proposed method is then used to demonstrate optimized dispatch of energy storage systems in a suitable four-wire unbalanced distribution test network. The contribution of losses in the neutral wire to the total losses is also determined for a test system under a range of operating conditions and various neutral earthing systems, highlighting the importance of considering this in a typical unbalanced distribution network.

The importance of power quality issues, due to the significant losses for poor power quality, has resulted in research being focused on extending the concept of state estimation techniques into power quality issues. Under the umbrella of power quality state estimation (PQSE) as a smart algorithm, this paper focuses on one type, transient state estimation (TSE). The formulation of a new three-phase transient state estimator is given and its application to a realistic system demonstrated. The accuracy of the new transient state estimator is investigated by application to a test system to identify the cause of a voltage dip/sag in the presence of 5% measurement noise (normally distributed) in all the measurements.

Smart‐meter data presents an opportunity for utilities to improve their database records, and develop a low‐voltage (LV) model which may be useful for outage management and fault detection, isolation and response, phase balancing, and network planning. In addition, impact assessment studies on new technologies can be performed. This study presents several contributions in the area of determining the topology of the LV distribution system. This is in terms of identifying the transformer a particular installation control point is connected to, and the phase if that customer is single‐phase. First, harmonic voltage correlation is proposed as it is more robust to noise and missing records than the prior algorithm of voltage correlation. Second, it is demonstrated that smart‐meter data can be used to determine the transformer/phase to which a customer is connected and update database records in this regard. To achieve this, a new algorithm based on correlation analysis with the Fisher Z transform is developed. Third, a method to estimate LV feeder and service main impedances is presented. Further work is necessary; however, the results from trials in Auckland, New Zealand are highly promising.